Computer Vision tasks like object detection, segmentation or tracking have reached near human precision and reliability with the application of deep learning techniques [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, [9]}. These deep learning techniques are mainly supervised in nature and need a huge amount of annotated data for proper training as well as learning proper generalization. In absence of enough data, the deep learning models often suffer from the overfitting problem. Collection and annotation of such huge amount of data is expensive and time consuming as well. In case of medical image data, the collection of data requires some expensive apparatus and the annotation needs to be done with the help of experienced medical personnel.
